Displaying a summary of media content items

ABSTRACT

The various implementations described herein include methods and systems for displaying a summary of media content items. In one aspect, a method is performed at a server system that includes processors and memory storing programs for execution by the processors. The server system: (1) detects presentation of a media content item at a first device in proximity to a second device, including receiving from the second device content identification information; (2) identifies the media content item; (3) identifies entities related to the identified media content item; (4) determines a level of interest with respect to a user of the second device, for each of the identified entities; (5) selects a subset of the identified plurality of entities based on the determined level of interest; and (6) sends to the second device, a summary of the media content item, for presenting at the second device.

RELATED APPLICATIONS

This application is a continuation of U.S. application Ser. No. 14/311,211, filed Jun. 20, 2014, entitled “Displaying a Summary of Media Content Items.”

This application is related to U.S. patent application Ser. No. 14/311,218, entitled “Displaying Information Related to Content Playing on a Device,” filed Jun. 20, 2014, and U.S. patent application Ser. No. 14/311,204, entitled “Displaying Information Related to Spoken Dialogue in Content Playing on a Device,” filed Jun. 20, 2014, which are incorporated by reference herein in their entirety.

TECHNICAL FIELD

The present application describes systems and methods for presenting information related to video content.

BACKGROUND

Users often want content, such as information, related to video content they are watching or related to video content they may otherwise be interested in, such as information related to spoken dialogue in the video content or information on people appearing in the video content. Typically, to obtain information related to video content, a user would need to visit a website using an Internet-enabled device. Existing methods for providing users with information related to video content are inefficient because they require users to take some action that is outside the viewing experience. Also, in these existing methods, information that is found may be presented in a way that is not conducive to ease of understanding or follow-up.

SUMMARY

The above deficiencies and other problems are reduced or eliminated by the disclosed methods and systems. The methods and systems described herein disclose systems and methods for displaying information on a client device that is related to content that is playing or have been played on a different or the same client device. Such methods and systems provide an effective way for users to be presented information related to content, such as videos, that is playing or have been played on a device. While a video is playing on a first client device, the first client device sends content information derived from the video to a server system. The server system identifies the video playing on the first client device by matching the content information to a content fingerprint. The server system then identifies entities, such as in-video quotations or people, related to the video and information relevant to these entities. The information is sent to a second client device for display, for example as a summary of the video.

In accordance with some implementations, methods, systems, and computer readable storage media are provided to generate a summary of media content items. Presentation of a media content item is detected. The media content item and one or more entities related to the media content item are identified. Respective levels of interest in the identified entities are determined based on one or more signals. A subset of the entities is selected based on the determined levels of interest. The selected subset of the entities is sent to a client device of a user, for presenting at the client device.

In accordance with some implementations, methods, systems, and computer readable storage media are provided to generate a summary of media content items. Presentation of a plurality of media content items is detected. The media content items, and, for each respective media content item, one or more entities related to the respective media content item, are identified. Respective levels of interest, with respect to a defined time period, in the identified entities are determined based on one or more signals. A subset of the entities is selected based on the determined levels of interest with respect to the defined time period. The selected subset of the entities is sent to a client device of a user for presenting at the client device.

BRIEF DESCRIPTION OF THE DRAWINGS

FIGS. 1A-1B are block diagrams illustrating distributed client-server systems in accordance with some implementations.

FIG. 2 is a block diagram illustrating the structure of an example server system according to some implementations.

FIG. 3A is a block diagram illustrating the structure of an example client device according to some implementations.

FIG. 3B is a block diagram illustrating the structure of an example client device according to some implementations.

FIG. 4 illustrates an example data structure according to some implementations.

FIG. 5 is a flowchart illustrating an overview of the process of displaying quotations content on a second device that is related to the content playing on a first device, in accordance with some implementations.

FIG. 6 is a flowchart illustrating an overview of the process of displaying a video content summary on a second device that is related to the content playing on a first device, in accordance with some implementations.

FIGS. 7A, 7B, and 7C are example screenshots in accordance with some implementations.

FIGS. 8A and 8B are example screenshots in accordance with some implementations.

FIG. 9 illustrates a flowchart for a method for identifying and storing quotations in accordance with some implementations.

FIGS. 10A-10B illustrate a flowchart for identifying quotations for presentation in accordance with some implementations.

FIG. 11 illustrates a flowchart for a method for presenting quotations in accordance with some implementations.

FIG. 12 illustrates a flowchart for a method for generating a summary of a media content item in accordance with some implementations.

FIG. 13 illustrates a flowchart for a method for generating a summary of media content items with respect to a time period in accordance with some implementations.

Like reference numerals refer to corresponding parts throughout the drawings.

DESCRIPTION OF IMPLEMENTATIONS

The methods and systems described herein disclose systems and methods for displaying content on a client device that is related to content playing or played on a client device (e.g., information related to quotations in the playing content, summaries of played content). Such methods and systems provide an effective way for viewers of video content to obtain relevant information about video content they are viewing, have viewed, or are otherwise interested in.

Reference will now be made in detail to various implementations, examples of which are illustrated in the accompanying drawings. In the following detailed description, numerous specific details are set forth in order to provide a thorough understanding of the invention and the described implementations. However, the invention may be practiced without these specific details. In other instances, well-known methods, procedures, components, and circuits have not been described in detail so as not to unnecessarily obscure aspects of the implementations.

FIG. 1A is a block diagram illustrating a distributed system 100 that includes: a client device 102, a client device 140, a communication network 104, a server system 106, a video content system 112, one or more content hosts 170, one or more social networks 172, and one or more search engines 174. The server system 106 is coupled to the client device 102, the client device 140, the video content system 112, content hosts 170, social networks 172, and search engines 174 by the communication network 104.

The functionality of the video content system 112 and the server system 106 can be combined into a single server system. In some implementations, the server system 106 is implemented as a single server system, while in other implementations it is implemented as a distributed system of multiple servers. Solely for convenience of explanation, the server system 106 is described below as being implemented on a single server system. In some implementations, the video content system 112 is implemented as a single server system, while in other implementations it is implemented as a distributed system of multiple servers. Solely, for convenience of explanation, the video content system 112 is described below as being implemented on a single server system.

The communication network(s) 104 can be any wired or wireless local area network (LAN) and/or wide area network (WAN), such as an intranet, an extranet, or the Internet. It is sufficient that the communication network 104 provides communication capability between the client devices 102 and 140, the server system 106, the video content system 112, the content hosts 170, and the social networks 172. In some implementations, the communication network 104 uses the HyperText Transport Protocol (HTTP) to transport information using the Transmission Control Protocol/Internet Protocol (TCP/IP). HTTP permits client devices 102 and 140 to access various resources available via the communication network 104. The various implementations described herein, however, are not limited to the use of any particular protocol.

In some implementations, the server system 106 includes a front end server 114 that facilitates communication between the server system 106 and the network 104. The front end server 114 receives content information 142 from the client 102 and/or the client 140. In some implementations, the content information 142 is a video stream or a portion thereof. In some implementations, the content information 142 is derived from a video stream playing on the client 102 (such as a portion of a video stream playing on the client 102 and one or more fingerprints of that portion). In some implementations, the front end server 114 is configured to send content to a client device 140. In some implementations, the front end server 114 is configured to send content links to content. In some implementations, the front end server 114 is configured to send or receive one or more video streams.

According to some implementations, a video or video stream is a sequence of images or frames representing scenes in motion. A video should be distinguished from an image. A video displays a number of images or frames per second. For example, a video displays 30 consecutive frames per second. In contrast, an image is not associated with any other images.

In some implementations, the server system 106 includes a user database 130 that stores user data. In some implementations, the user database 130 is a distributed database.

In some implementations, the server system 106 includes a content identification module 118 that includes modules to receive content information 142 from the client 102 and/or the client 140, match the content information to a content fingerprint in the fingerprint database 120, and identify the video content (e.g., a “video content item,” such as a movie, television series episode, video clip, or any other distinct piece of video content) being presented at the client device 102 based on the matching of the content information and the content fingerprint. In some implementations, the content identification module also identifies the current position in the video content (e.g., the position or how far in the video content is being presented on the client device 102). The identity of the video content and the current position in the video content is passed onto the entities module 144, which identifies one or more entities related to the identified video content in an entities database 122.

In some implementations, the server system 106 includes a fingerprint database 120 that stores content fingerprints. As used herein, a content fingerprint is any type of condensed or compact representation, or signature, of the content of a video stream and/or audio stream and/or subtitles/captions data corresponding to the video stream and/or audio stream. In some implementations, a fingerprint may represent a clip (such as several seconds, minutes, or hours) or a portion of a video stream or audio stream or the corresponding subtitles/captions data. Or, a fingerprint may represent a single instant of a video stream or audio stream or subtitles/captions data (e.g., a fingerprint of single frame of a video or of the audio associated with that frame of video or the subtitles/captions corresponding to that frame of video). Furthermore, since video content changes over time, corresponding fingerprints of that video content will also change over time. In some implementations, the fingerprint database 120 is a distributed database.

In some implementations, the client device 102 includes a video module 110 that receives video content 126 from the video content system 112, extracts content information 142 from video content 126 (e.g., a video stream) that is playing on the client 102 and sends the content information 142 to the server 106.

The client device 102 is any suitable computer device that in some implementations is capable of connecting to the communication network 104, receiving video content (e.g., video streams), extracting information from video content and presenting video content on the display device 108. In some implementations, the client device 102 is a set top box that includes components to receive and present video streams. For example, the client device 102 can be a set top box for receiving cable TV and/or satellite TV, a digital video recorder (DVR), a digital media receiver, a TV tuner, a computer, and/or any other device that outputs TV signals. In some other implementations, the client device 102 is a computer, laptop computer a tablet device, a netbook, a mobile phone, a smartphone, tablet device, a gaming device, a multimedia player device, or any other device that is capable of receiving video content (e.g., as video streams through the network 104). In some implementations, the client device 102 displays a video stream on the display device 108. In some implementations the client device 102 is a conventional TV display that is not connected to the Internet and that displays digital and/or analog TV content via over the air broadcasts or a satellite or cable connection.

In some implementations, the display device 108 can be any display for presenting video content to a user. In some implementations, the display device 108 is the display of a television, or a computer monitor, that is configured to receive and display audio and video signals or other digital content from the client 102. In some implementations, the display device 108 is an electronic device with a central processing unit, memory and a display that is configured to receive and display audio and video signals or other digital content form the client 102. For example, the display device can be a LCD screen, a tablet device, a mobile telephone, a projector, or other type of video display system. The display 108 can be coupled to the client 102 via a wireless or wired connection.

In some implementations, the client device 102 receives video content 126 via a TV signal 138. As used herein, a TV signal is an electrical, optical, or other type of data transmitting medium that includes audio and/or video components corresponding to a TV channel. In some implementations, the TV signal 138 is a terrestrial over-the-air TV broadcast signal or a signal distributed/broadcast on a cable-system or a satellite system. In some implementations, the TV signal 138 is transmitted as data over a network connection. For example, the client device 102 can receive video streams from an Internet connection. Audio and video components of a TV signal are sometimes referred to herein as audio signals and video signals. In some implementations, a TV signal corresponds to a TV channel that is being displayed on the display device 108.

In some implementations, a TV signal carries information for audible sound corresponding to an audio track on a TV channel. In some implementations, the audible sound is produced by speakers associated with the display device 108 or the client device 102 (e.g. speakers 109).

In some implementations, a TV signal carries information or data for subtitles or captions (e.g., closed captions) that correspond to spoken dialogue in the audio track. The subtitles or captions are a textual transcription of spoken dialogue in the video content. The subtitles or captions can be presented concurrently along with the corresponding video content. For convenience, subtitles and captions are hereinafter referred to collectively as “subtitles,” and subtitles/captions data as “subtitles data.”

The client device 140 may be any suitable computer device that is capable of connecting to the communication network 104, such as a computer, a laptop computer, a tablet device, a netbook, an internet kiosk, a personal digital assistant, a mobile phone, a gaming device, or any other device that is capable of communicating with the server system 106. The client device 140 typically includes one or more processors, non-volatile memory such as a hard disk drive and a display. The client device 140 may also have input devices such as a keyboard and a mouse (as shown in FIG. 3). In some implementations, the client device 140 includes touch screen displays.

In some implementations, the client device 140 is connected to a display device 128. The display device 128 can be any display for presenting video content to a user. In some implementations, the display device 128 is the display of a television, or a computer monitor, that is configured to receive and display audio and video signals or other digital content from the client 128. In some implementations, the display device 128 is an electronic device with a central processing unit, memory and a display that is configured to receive and display audio and video signals or other digital content from the client 140. In some implementations, the display device 128 is a LCD screen, a tablet device, a mobile telephone, a projector, or any other type of video display system. In some implementations, the client device 140 is connected to the display device 128. In some implementations, the display device 128 includes, or is otherwise connected to, speakers capable of producing an audible stream corresponding to the audio component of a TV signal or video stream.

In some implementations, the client device 140 is connected to the client device 102 via a wireless or wired connection. In some implementations where such connection exists, the client device 140 optionally operates in accordance with instructions, information and/or digital content (collectively second screen information) provided by the client device 102. In some implementations, the client device 102 issues instructions to the client device 140 that cause the client device 140 to present on the display 128 and/or the speaker 129 digital content that is complementary, or related to, digital content that is being presented by the client 102 on the display 108. In some other implementations, the server 106 issues instructions to the client device 140 that cause the client device 140 to present on the display 128 and/or the speaker 129 digital content that is complementary, or related to, digital content that is being presented by the client 102 on the display 108.

In some implementations, the client device 140 includes a microphone that enables the client device to receive sound (audio content) from the client 102 as the client 102 plays the video content 126. The microphone enables the client device 102 to store the audio content/soundtrack that is associated with the video content 126 as it is played/viewed. In the same manner as described herein for the client 102, the client device 140 can store this information locally and then send to the server 106 content information 142 that is any one or more of: fingerprints of the stored audio content, the audio content itself, portions/snippets of the audio content, or fingerprints of the portions of the audio content. In this way, the server 106 can identify the video content 126 being played on client 102 even if the electronic device on which the content is being displayed/viewed is not an Internet-enabled device, such as an older TV set; is not connected to the Internet (temporarily or permanently) so is unable to send the content information 142; or does not have the capability to record or fingerprint media information related to the video content 126. Such an arrangement (i.e., where the second screen device 140 stores and sends the content information 142 to the server 106) allows a user to receive from the server 106 second screen content triggered in response to the content information 142 no matter where the viewer is watching TV and information related to the video content 126, such as information related to entities in the video content 126.

In some implementations, the content information 142 sent to the server 106 from either the client 102 or 140 includes any one or more of: fingerprints of the stored subtitles data, the subtitles data itself, portions/snippets of the subtitles data, or fingerprints of the portions of the subtitles data. In this way, the server 106 can identify the video content 126 being played on the client 102 even if, for example, the volume level on the client 102 is too low for the audio content to be audibly detected by the client device 140, the audio content as output by the client 102 is distorted (e.g., because of poor transmission quality from the video content system 112, because of a lag in processing capability at the client 102), or if the speakers 109 are otherwise not functional.

In some implementations, the client device 140 includes one or more applications 127. As discussed in greater detail herein, the one or more applications 127 receive and present information received from the server 106, such as entities in video content and information about entities in video content (collectively referred to as “entity information”). In some implementations, the applications 127 include an assistant application. An assistant application obtains and presents information relevant to the user based on a variety of signals, including, but not limited to, the user's demographic information, the current location of the device and/or the user, the user's calendar, the user's contact list, the user's social network(s), the user's search history, the user's web browsing history, the device's and/or the user's location history, the user's stated preferences, the user's content viewing history, and the content being currently presented to the user.

The server 106 includes an entities database or repository 122. The entities database 122 is a database of entities associated with video content. As used herein, an entity is any distinct existence or thing that is associated with video content. In some implementations, entities include, without limitation, titles, people, places, music, things, products, quotations, and awards. For example, titles include movie titles, series titles (e.g., television series titles), and episode titles (e.g., television episodes titles). People include cast members (e.g., actors), crew members (e.g., director, producer, music composer, etc.), in-story characters, competition contestants, competition judges, hosts, guests, and people mentioned. Places include in-story locations, filming locations, and locations mentioned. Music include songs and compositions used in the video content. Things include in-story objects (e.g., lightsabers in “Star Wars”). Products include any good, service, or item mentioned or shown in video content (e.g., mentioned book, products included in video content due to product placement). Quotations include pieces of spoken dialogue from video content, such as lines and catchphrases spoken by characters or non-fictional people in video content (e.g., “May the Force be with you.”). Awards include any awards associated with a piece of video content and its entities (e.g., best actor, best director, best song, etc.). It should be appreciated that these examples are non-exhaustive and other categories of entities are possible.

In some implementations, the entities database 122 also includes a graph network that indicates associations between entities. For example, a movie entity (e.g., the movie title entity as the entity representing to the movie) is linked to its cast member entities, crew member entities, in-story location entities, quotation entities, and so on. The graph network is implemented using any suitable data structure.

In some implementations, the entities database 122 also includes information regarding when an entity appears, is mentioned, or is said (e.g., in the case of a quotation) in a video content item. For example, for a movie entity, the entities database 122 stores information on, for example, when particular characters or cast members appear (e.g., are actually on-screen), is in the active scene even if not on-screen for entire duration of the active scene) in the movie. Such information may be stored as time ranges within the video content item (e.g., a time range of 22:30-24:47 means that a character or cast member appears in the video content item from the 22 minutes 30 seconds mark to the 24 minutes 47 seconds mark). Similarly, the entities database 122 stores information on when in a video content item a place appears or is mentioned, when a song or composition is played, when a quotation is spoken, when a thing appears or is mentioned, when a product appears or is mentioned, and so forth.

In some implementations, entities in the entities database 122 are also associated with non-entities outside of the entities database. For example, a person entity in the entities database 122 may include links to web pages of news stories associated with the person.

The server 106 includes an entities module 144, summaries module 146, quotations module, and popularity module 150. The entities module 144 identifies and extracts entities related to video content and stores the extracted entities in the entities database 122. In some implementations, the entities module 144 extracts entities related to video content from video content (e.g., from content information 142) and from other sources (e.g., web pages hosted by content hosts 170). In some implementations, the entities module 144 also selects one or more entities from the entities database 122 and provides them to the front end server 114, for sending to a client device (e.g., client device 140) for presentation.

The summaries module 146 generates summaries of video content. A summary, as used herein, is a listing of entities associated with video content (e.g., entities that appear or are mentioned in video content). In some implementations, entities included in a summary are entities associated with a video content item that are determined to be popular in the aggregate based on one or more popularity criteria, further details of which are described below; the summary is generated with respect to a video content item and is not personalized to a particular user. In some implementations, entities included a summary are entities associated with a video content item that are determined to be popular in the aggregate as well as with a particular user; the summary is generated with respect to a video content item and is personalized to a particular user. In some implementations, entities included in a summary are entities associated with video content (but not necessarily all associated with the same video content item) that are determined to be popular in the aggregate for a defined time period (e.g., a certain month, a certain day, a certain week, particular hours (e.g., “prime time” hours) in a certain day, etc.); the summary is generated not with respect to a particular video content item.

The quotations module 148 identifies quotations in video content. Video content has numerous spoken dialogue. However, not all lines or phrases of spoken dialogue are interesting or popular or well-known or invocative of particular titles or people. The quotation module 148, in some implementations in conjunction with a popularity module 150, determines which lines or phrases of spoken dialogue (i.e., quotations) are popular or well-known or so forth (e.g., based on, for example, online mentions and sharing, etc.), and thus stored as distinct entities in the entities database 122. The quotations module 148 analyzes non-video content, such as documents (e.g., web pages) and social networks, hosted by content hosts 170 and social networks 172, to determine which lines and phrases of spoken dialogue in video content are being shared, mentioned, or commented upon, and thus deserve distinction as a distinct quotation entity.

The popularity module 150 determines the popularity of entities based on one or more criteria. In some implementations, the popularity module 150 determines popularity in real-time (e.g., popularity within the last hour) as well as historical popularity or popularity over a longer time horizon (e.g., popularity year-to-date, popularity all-time, etc.).

The distributed system 100 also includes one or more content hosts 170, one or more social networks 172, and one or more search engines 174. The content hosts 170 hosts content that can be used to determine popularity of entities, such as web pages where entities may be mentioned and commented upon. Similarly, social networks 172 also includes content in which entities may be mentioned and commented upon (e.g., in user comments and posts). Further, in the social networks 172, content may be shared, which provides another metric for popularity of entities. Search engines 174 may receive queries corresponding to entities from the client devices 102 or 140, and return related information.

FIG. 1B depicts a distributed system 180 that is similar to the distributed system 100 depicted in FIG. 1A. In FIG. 1B, the features of client devices 102 and 140 (FIG. 1A) are subsumed into a client device 182. In the distributed system 180, the client device 182 device receives and presents the video content 126. The client device 182 sends the content information 142 to the server 106. The server 106 identifies the video content and sends entity information 132 to the client device 182 for presentation. In other aspects, the distributed system 180 is same as or similar to the distributed system 100. Thus, the details are not repeated here.

FIG. 2 is a block diagram illustrating a server system 106, in accordance with some implementations. The server system 106 typically includes one or more processing units (CPU's) 202, one or more network or other communications interfaces 208, memory 206, and one or more communication buses 204 for interconnecting these components. The communication buses 204 optionally include circuitry (sometimes called a chipset) that interconnects and controls communications between system components. Memory 206 includes high-speed random access memory, such as DRAM, SRAM, DDR RAM or other random access solid state memory devices; and may include non-volatile memory, such as one or more magnetic disk storage devices, optical disk storage devices, flash memory devices, or other non-volatile solid state storage devices. Memory 206 may optionally include one or more storage devices remotely located from the CPU(s) 202. Memory 206, including the non-volatile and volatile memory device(s) within memory 206, comprises a non-transitory computer readable storage medium. In some implementations, memory 206 or the non-transitory computer readable storage medium of memory 206 stores the following programs, modules and data structures, or a subset thereof including an operation system 216, a network communication module 218, a content identification module 118, a fingerprint database 120, an entities database 122, a user database 130, an entities module 144, a summaries module 146, a quotations module 148, and a popularity module 150.

The operating system 216 includes procedures for handling various basic system services and for performing hardware dependent tasks.

The network communication module 218 facilitates communication with other devices via the one or more communication network interfaces 208 (wired or wireless) and one or more communication networks, such as the Internet, other wide area networks, local area networks, metropolitan area networks, and so on.

The fingerprint database 120 stores one or more content fingerprints 232. A fingerprint 232 includes a name 234, fingerprint audio information 236 and/or fingerprint video information 238, and a list of associated files 239. The name 234 identifies the respective content fingerprint 232. For example, the name 234 could include the name of an associated television program, movie, or advertisement. In some implementations, the fingerprint audio information 236 includes a fingerprint or other compressed representation of a clip (such as several seconds, minutes, or hours) of the audio content of a video stream or an audio stream. In some implementations, the fingerprint video information 238 includes a fingerprint of a clip (such as several seconds, minutes, or hours) of a video stream. In some implementations, the fingerprint 232 includes a fingerprint or other representation of a portion of the subtitles data of a video stream. Fingerprints 232 in the fingerprint database 120 are periodically updated.

The user database 124 includes user data 240 for one or more users. In some implementations, the user data for a respective user 240-1 includes a user identifier 242 and demographic information 244. The user identifier 242 identifies a user. For example, the user identifier 242 can be an IP address associated with a client device 102 or an alphanumeric value chosen by the user or assigned by the server that uniquely identifies the user. The demographic information 244 includes the characteristics of the respective user. The demographic information may include may be one or more of the group consisting of age, gender, income, geographic location, education, wealth, religion, race, ethic group, marital status, household size, employment status, and political party affiliation. In some implementations, the user data for a respective user also includes one or more of the following: a search history (e.g., search queries the user has submitted to search engines), a content browsing history (e.g., web pages viewed by the user), and a content consumption history (e.g., videos the user has viewed).

The content identification module 118 receives content information 142 from the client 102 or 140, and identifies the video content being presented at the client 102 or 140. The content identification module 118 includes a fingerprint matching module 222. In some implementations, the content identification module 118 also includes a fingerprint generation module 221, which generates fingerprints from the content information 142 or other media content saved by the server.

The fingerprint matching module 222 matches at least a portion of the content information 142 (or a fingerprint of the content information 142 generated by the fingerprint generation module) to a fingerprint 232 in the fingerprint database 120. The matched fingerprint 242 is sent to the entities module 144, which retrieves the entities associated with the matched fingerprint 242. The fingerprint matching module 222 includes content information 142 received from the client 102. The content information 142 includes audio information 224, video information 226, a user identifier 229, and optionally subtitles data (not shown). The user identifier 229 identifiers a user associated with the client 102 or 140. For example, the user identifier 229 can be an IP address associated with a client device 102 or an alphanumeric value chosen by the user or assigned by the server that uniquely identifies the user. In some implementations, the content audio information 224 includes a clip (such as several seconds, minutes, or hours) of a video stream or audio stream that was played on the client device 102. In some implementations, the content video information 226 includes a clip (such as several seconds, minutes, or hours) of a video stream that was played on the client device 102.

The entities database 122 includes entities associated with video content. The entities database 122 is further described below, with reference to FIG. 4.

The entities module 144 selects entities from the entities database that are associated with a video content item, based on the matched fingerprint 242 or other criteria. The selected entities may be a subset of the entities referenced in the matched fingerprint 242 (e.g., the entities module 144 selects the most popular of the entities referenced in the matched fingerprint 242).

The summaries module 146 generates summaries of video content. The summaries include entities in a video content item that are popular with respect to a video content item or with respect to a defined time period.

The quotations module 148 identifies quotations in video content from the video content themselves (e.g., using the subtitles data) and from non-video content (e.g., mentions, shares, and commentary on quotations in web pages and social networks).

Popularity module 150 determines and updates the popularities of entities in the entities database 122.

In some implementations, the summaries module 146, quotations module 148, and popularity module 150 are sub-modules of entities module 144.

Each of the above identified elements may be stored in one or more of the previously mentioned memory devices, and each of the modules or programs corresponds to a set of instructions for performing a function described above. The set of instructions can be executed by one or more processors (e.g., the CPUs 202). The above identified modules or programs (i.e., content identification module 118) need not be implemented as separate software programs, procedures or modules, and thus various subsets of these modules may be combined or otherwise re-arranged in various implementations. In some implementations, memory 206 may store a subset of the modules and data structures identified above. Furthermore, memory 206 may store additional modules and data structures not described above.

Although FIG. 2 shows a server system, FIG. 2 is intended more as functional description of the various features which may be present in a set of servers than as a structural schematic of the implementations described herein. In practice, and as recognized by those of ordinary skill in the art, items shown separately could be combined and some items could be separated. For example, some items (e.g., operating system 216 and network communication module 218) shown separately in FIG. 2 could be implemented on single servers and single items could be implemented by one or more servers. The actual number of servers used to implement the server system 106 and how features are allocated among them will vary from one implementation to another, and may depend in part on the amount of data traffic that the system must handle during peak usage periods as well as during average usage periods.

FIG. 3A is a block diagram illustrating a client device 102, in accordance with some implementations. The client device 102 typically includes one or more processing units (CPU's) 302, one or more network or other communications interfaces 308, memory 306, and one or more communication buses 304, for interconnecting these components. The communication buses 304 optionally include circuitry (sometimes called a chipset) that interconnects and controls communications between system components. The client device 102 may also include a user interface comprising a display device 313 and a keyboard and/or mouse (or other pointing device) 314. Memory 306 includes high-speed random access memory, such as DRAM, SRAM, DDR RAM or other random access solid state memory devices; and may include non-volatile memory, such as one or more magnetic disk storage devices, optical disk storage devices, flash memory devices, or other non-volatile solid state storage devices. Memory 306 may optionally include one or more storage devices remotely located from the CPU(s) 302. Memory 306, or alternatively the non-volatile memory device(s) within memory 306, comprises a non-transitory computer readable storage medium. In some implementations, memory 306 or the computer readable storage medium of memory 306 store the following programs, modules and data structures, or a subset thereof including operation system 316, network communication module 318, a video module 110 and data 320.

The client device 102 includes a video input/output 330 for receiving and outputting video streams. In some implementations, the video input/output 330 is configured to receive video streams from radio transmissions, satellite transmissions and cable lines. In some implementations the video input/output 330 is connected to a set top box. In some implementations, the video input/output 330 is connected to a satellite dish. In some implementations, the video input/output 330 is connected to an antenna. In some implementations, the client device 102 receives the video stream through the network interface 308 (e.g., receiving the video stream through the Internet), as opposed to through a video input.

In some implementations, the client device 102 includes a television tuner 332 for receiving video streams or TV signals.

The operating system 316 includes procedures for handling various basic system services and for performing hardware dependent tasks.

The network communication module 318 facilitates communication with other devices via the one or more communication network interfaces 308 (wired or wireless) and one or more communication networks, such as the Internet, other wide area networks, local area networks, metropolitan area networks, and so on.

The data 320 includes video streams 126.

The video module 126 derives content information 142 from a video stream 126. In some implementations, the content information 142 includes audio information 224, video information 226, a user identifier 229 or any combination thereof. The user identifier 229 identifies a user of the client device 102. For example, the user identifier 229 can be an IP address associated with a client device 102 or an alphanumeric value chosen by the user or assigned by the server that uniquely identifies the user. In some implementations, the audio information 224 includes a clip (such as several seconds, minutes, or hours) of a video stream or audio stream. In some implementations, the video information 226 may include a clip (such as several seconds, minutes, or hours) of a video stream. In some implementations, the content information 142 includes subtitles data corresponding to the video stream. In some implementations, the video information 226 and audio information 224 are derived from a video stream 126 that is playing or was played on the client 102. The video module 126 may generate several sets of content information 142 for a respective video stream 346.

Each of the above identified elements may be stored in one or more of the previously mentioned memory devices, and each of the modules or programs corresponds to a set of instructions for performing a function described above. The set of instructions can be executed by one or more processors (e.g., the CPUs 302). The above identified modules or programs (i.e., sets of instructions) need not be implemented as separate software programs, procedures or modules, and thus various subsets of these modules may be combined or otherwise re-arranged in various implementations. In some implementations, memory 306 may store a subset of the modules and data structures identified above. Furthermore, memory 306 may store additional modules and data structures not described above.

Although FIG. 3A shows a client device, FIG. 3A is intended more as functional description of the various features which may be present in a client device than as a structural schematic of the implementations described herein. In practice, and as recognized by those of ordinary skill in the art, items shown separately could be combined and some items could be separated.

FIG. 3B is a block diagram illustrating a client device 140, in accordance with some implementations. The client device 140 typically includes one or more processing units (CPU's) 340, one or more network or other communications interfaces 345, memory 346, and one or more communication buses 341, for interconnecting these components. The communication buses 341 optionally include circuitry (sometimes called a chipset) that interconnects and controls communications between system components. The client device 140 may also include a user interface comprising a display device 343 and a keyboard and/or mouse (or other pointing device) 344. Memory 346 includes high-speed random access memory, such as DRAM, SRAM, DDR RAM or other random access solid state memory devices; and may include non-volatile memory, such as one or more magnetic disk storage devices, optical disk storage devices, flash memory devices, or other non-volatile solid state storage devices. Memory 346 may optionally include one or more storage devices remotely located from the CPU(s) 340. Memory 346, or alternatively the non-volatile memory device(s) within memory 346, comprises a non-transitory computer readable storage medium. In some implementations, memory 346 or the computer readable storage medium of memory 346 store the following programs, modules and data structures, or a subset thereof including operation system 347, network communication module 348, graphics module 349, and applications 355.

The operating system 347 includes procedures for handling various basic system services and for performing hardware dependent tasks.

The network communication module 348 facilitates communication with other devices via the one or more communication network interfaces 345 (wired or wireless) and one or more communication networks, such as the Internet, other wide area networks, local area networks, metropolitan area networks, and so on.

The client device 140 includes one or more applications 355. In some implementations, the applications 355 include a browser application 355-1, a media application 355-2, and an assistant application 355-3. The browser application 355-1 displays web pages. The media application 355-2 plays videos and music, displays images and manages playlists 356. The assistant application (which may also be referred to as an “intelligent personal assistant” application) 355-3 displays information that is relevant to the user at the moment (e.g., entities 357, provided by the server 106, related to the video the user is watching; upcoming appointments; traffic on a route to be travelled) and perform tasks or services relevant to the user or requested by the user (e.g., sending alerts to notify friends of tardiness to a dinner appointment, schedule updating, calling the restaurant). The applications 328 are not limited to the applications discussed above.

Each of the above identified elements may be stored in one or more of the previously mentioned memory devices, and each of the modules or programs corresponds to a set of instructions for performing a function described above. The set of instructions can be executed by one or more processors (e.g., the CPUs 340). The above identified modules or programs (i.e., sets of instructions) need not be implemented as separate software programs, procedures or modules, and thus various subsets of these modules may be combined or otherwise re-arranged in various implementations. In some implementations, memory 306 may store a subset of the modules and data structures identified above. Furthermore, memory 306 may store additional modules and data structures not described above.

Although FIG. 3B shows a client device, FIG. 3B is intended more as functional description of the various features which may be present in a client device than as a structural schematic of the implementations described herein. In practice, and as recognized by those of ordinary skill in the art, items shown separately could be combined and some items could be separated.

FIG. 4 illustrates entities data structures 426 stored in the entities database 122, according to some implementations. A respective entity 428 includes a entity identifier (entity ID) 448, entity type 450, entity name 452, references to other entities 454, references to non-entities 458, popularity metrics 460, and optionally, additional information. In some implementations, the entity ID 448 uniquely identifies a respective entity 428. The entity type 450 identifies the type of the entity 428. For example, the entity type 450 for a respective entity 428 in the entities database 122 indicates that the respective entity 428 is a title, person, place, music, thing, product, quotation, and award. In some implementation, the entity type 450 also indicates sub-types (e.g., for people, cast or crew or character or contestant or judge or host or guest or mentioned person). The entity name 452 names the entity. For example, the entity name, depending on the entity, is the title of the movie or television show, person name, place name, song or composition name, name of a thing, a product name, the actual words of a quotation, or the award name. References to other entities 454 indicate references to other entities 428 (e.g., by their entity IDs 448). For example, an entity 428 corresponding to a movie title includes references 454 to the movie's cast members, crew members, characters, places, and so on. A quotation entity includes references to the video content (movie, televisions show, etc.) in which the quotation is spoken, and the person (actor, character, etc.) who spoke the quotation in the video content. When appropriate, the references to other entities include data on instances 456 when the other entities appear or are mentioned. For example, the instances 456 data for a movie title entity include time ranges for when a cast member or a character appears, or when a product is mentioned, and so on. References to non-entities 458 include references to content not stored as entities in the entities database 122 that are nevertheless related to the entity 428 (e.g., links to web pages mentioning the entity). The popularity metrics 460 provide a measure of the importance of an entity file 428. In some implementations, the metrics 460 are determined by the popularity module 150. In some implementations, the popularity metrics include both historical and real-time popularity.

Displaying Quotations

FIG. 5 is a flow diagram illustrating a process 500 of displaying quotations content on a second device that is related to the content played on a first device, according to some implementations. FIG. 5 provides an overall view of methods 1000 and 1100 which is discussed in more detail in the discussion of in FIGS. 10A-11. A video content system 112 sends a video stream to a client 102 (501). The video stream is received and displayed by the client device 102 (502). While the video stream is played, content information from the video stream is determined and sent to a server 106 (506). As described elsewhere in this application, in some implementations the content information from the video stream includes one or more clips (such as several seconds, minutes or hours) of audio and/or video components of the video stream or the corresponding subtitles data, or fingerprints or other signatures generated by the client device 102 from one or more clips of the audio and/or video components of the video stream and/or the corresponding subtitles data. In some implementations, the content information is formatted so it can be readily compared to content fingerprints stored on the server. The server 106 receives the content information and matches the content information to a content fingerprint (508).

In some implementations, while the video stream is played, the client device 140 determines content information from the audio output, from the client device 102, corresponding to the audio component of the video stream (e.g., a microphone on the client 140 picks up the audio output from the client 102). The client 140 determines the content information and sends the content information to the server 106; the client 140 performs step 506 instead of client 102.

In some implementations, the content fingerprints are generated by the server (e.g., using the fingerprint generation module 221) prior to run time from media content (e.g., audio and/or video clips, or video frames) uploaded by a third party user. In some implementations, the content fingerprints are generated by the server (e.g., using the fingerprint generation module 221) in real-time (e.g., live) or prior to run time from media content (e.g., audio and/or video clips, or video frames) received from the video content system 112.

One or more quotations, and optionally one or more other entities, associated with the matched fingerprint are determined (512); the quotations are lines or phrases spoken in the video content, and the other entities may include actors/characters who spoke the quotations in the video content. In some implementations, the determined quotations are the most popular quotations for the video content item or proximate to the portion of the video content item being presented. As used herein, proximate to a portion of a video content item means proximate in time to the currently presented portion within the video content item. For example, if the video content item is playing at the 20:00 mark, then quotations proximate to the 20:00 mark, or the portion including such, would include quotations that are spoken within a defined time range (e.g., plus/minus 15 minutes) from the 20:00 mark. The quotations, one or more corresponding affordances, and optionally the other entities, are sent to the client 140 (514). In some implementations, the quotations and affordances are sent to the client 140 directly, via the client's connection to the communications network 104, or indirectly, via a connection between the client 140 and the client 102. In some implementations, in lieu of sending affordances to the client 140, the server 106 sends instructions to an application configured to present the quotations and other entities (e.g., assistant application 355-3, FIG. 3B) to generate and present the corresponding affordances at the client 140. The client device 140 receives the quotations, affordances, and, optionally, the other entities (516). The quotations and affordances, and optionally the other entities, are presented (518). In some implementations, the one or more quotations and affordances are displayed on the display device 128 associated with the client device 140 in coordination in time with the video stream 126 being displayed by the client 102. For example, the quotations presented include quotations that have been spoken within a predefined time period preceding the current presentation position in the video stream (e.g., the last half hour from the current position). In some implementations, the quotations include quotations that are subsequent to the current presentation position in the video stream. These upcoming quotations may be held back from display until the positions in the video stream where the upcoming quotations are spoken are presented, in order to prevent spoiling the plot of the video content for the user.

The affordances include affordances for activating various operations or actions on a respective quote. In some implementations, the respective affordances correspond to respective actions; the user selects a quotation and then activates a respective affordance to activate the corresponding action for the selected quotation. In some other implementations, each displayed quotation has a respective set of one or more affordances; the user activates an affordance for a respective quotation to activate a menu of actions for the respective quotation or to activate an action for the respective quotation. The actions and operations that can be activated with respect to a quotation are further described below.

-   -   Displaying Summaries of Popular Entities

FIG. 6 is a flow diagram illustrating a process 600 of displaying summaries on a second device that is related to the content played on a first device, according to some implementations. FIG. 6 provides an overall view of methods 1200 and 1300 which is discussed in more detail in the discussion of in FIGS. 12-13. A video content system 112 sends a video stream to a client 102 (601). The video stream is received and displayed by the client device 102 (602). While the video stream is played, content information from the video stream is determined and sent to a server 106 (606). As described elsewhere in this application, in some implementations the content information from the video stream includes one or more clips (such as several seconds, minutes or hours) of audio and/or video components of the video stream or the corresponding subtitles data, or fingerprints or other signatures generated by the client device 102 from one or more clips of the audio and/or video components of the video stream and/or the corresponding subtitles data. In some implementations, the content information is formatted so it can be readily compared to content fingerprints stored on the server. The server 106 receives the content information and matches the content information to a content fingerprint (608).

In some implementations, while the video stream is played, the client device 140 determines content information from the audio output, from the client device 102, corresponding to the audio component of the video stream (e.g., a microphone on the client 140 picks up the audio output from the client 102). The client 140 determines the content information and sends the content information to the server 106; the client 140 performs step 606 instead of client 102.

In some implementations, the content fingerprints are generated by the server (e.g., using the fingerprint generation module 221) prior to run time from media content (e.g., audio and/or video clips, or video frames) uploaded by a third party user. In some implementations, the content fingerprints are generated by the server (e.g., using the fingerprint generation module 221) in real-time (e.g., live) or prior to run time from media content (e.g., audio and/or video clips, or video frames) received from the video content system 112.

A summary associated with the matched fingerprint is determined (612); the summary includes the most popular entities for a video content item. The summary is sent to the client 140 (614). In some implementations, the summary is sent to the client 140 directly, via the client's connection to the communications network 104, or indirectly, via a connection between the client 140 and the client 102. The client device 140 receives the summary (616). The summary is presented (618). In some implementations, the summary is displayed on the display device 128 after presentation of the video stream 126 by the client 102 has completed (e.g., at the end of the video content item). In some other implementations, the summary is presented at a time that is not dependent on presentation or end of presentation of any particular video content item.

Example UIs for Displaying Quotations

FIGS. 7A, 7B, and 7C illustrate example screen shots in accordance with some implementations. FIGS. 7A, 7B, and 7C each illustrate screen shots of a first client 102 and a second client 140. The first client 102 plays video content, while the second client 140 displays quotations content related to the video content playing on the first client 102. The illustrations in FIGS. 7A, 7B, and 7C should be viewed as example but not restrictive in nature. In some implementations, the example screen shots are generated by instructions/applications downloaded to the second client device 140 by the server 106 in response to the server 106 matching client fingerprints to content fingerprints stored on the server. In some implementations, the example screen shots are generated by instructions/applications that are stored on the second client device 140 (such as a browser, an assistant application, or other pre-configured application) in response to an instruction from the server 106 to display particular content in response to the server 106 matching client fingerprints to content fingerprints stored on the server.

FIG. 7A illustrates screenshots of the first client device 102 and the second client device 140. The first client 102 displays a television series episode 702 and the second client 140 displays an application 706 (e.g., an assistant application), one or more quotations 708 spoken in the episode 702, and affordances 710 corresponding to the respective quotations 708. While the episode 702 is played on the first client 102, the first client 102 sends content information derived from the episode 702 to the server system 106. Alternatively, the second client 140 sends content information derived from audio output, from the first client 102, corresponding to the episode 702 to the server system 106. The server system 106 matches the content information to a content fingerprint in order to identify the episode 702. After identifying a content fingerprint that matches the content information, the server 106 determines one or more quotations related to the episode 702 (spoken in the episode) and sends the quotations and corresponding affordances to the second client device 140 for presentation. The second client device 140 presents the quotations 708 and corresponding affordances 710. The quotations 708 also include respective timestamps for when the quotations are spoken in the episode 702. In some implementations, additional information (e.g., entities that spoke the quotations) are sent along with the quotations and affordances.

In some implementations, a user selects a quotation (e.g., by clicking on or tapping on a quotation 708) to bring up additional information on the quotation. For example, if quotation 708-1 is selected, the box for quotation 708-1 expands to display additional information, as shown in FIG. 7B. In the expanded box for quotation 708-1, more information associated with the quotation is presented, such as the entity (the actor, the character) that spoke the quotation in the episode 702.

The user may select the affordance 710 for quotation 708-1 to bring up a menu 712 of actions with respect to the quotation, as shown in FIG. 7C. The menu 712 includes various actions on the quotation 708-1 that can be activated. For example, the user can request to see more entities related to the quotation 708-1 (and have those entities displayed on the display), share the quotation 708-1 (e.g., in a social network 172, by email, by text message, and so on), play a video clip that includes the quotation 708-1 (e.g., a portion of episode 702), search the quotation 708-1 in a search engine 174 (e.g., submit the quotation 708-1 as a query to the search engine 174), search an entity related to the quotation 708-1 (e.g., the actor or character that spoke the quotation, the episode and series in which the quote was spoken) in a search engine 174, comment on the quotation 708-1, and indicate interest in the episode 702 and include the quotation 708-1 in the indication of interest. In some implementations, activation of the comment action triggers display of a text input interface on the display at the second client 140 for inputting a comment on the quotation 708-1, which may be stored at the server system 106. In some implementations, an activation of the indication of interest action triggers a submission of an indication of interest (e.g., a like, a status post) for the episode 702 to a social network 172, and the indication of interest includes the quotation 708-1.

Example UIs for Displaying Summaries of Popular Entities

FIGS. 8A and 8B illustrate example screen shots in accordance with some implementations. FIG. 8A illustrates screen shots of a first client 102 and a second client 140, and FIG. 8B illustrates a screen shot of the second client 140. In FIG. 8A, the first client 102 plays video content, and after the video content is played at the first client 102, the second client 140 displays a summary of entities related to the video content played on the first client 102. In FIG. 8B, the second client 140 displays a summary of entities related to video content with respect to a defined time period. The illustrations in FIGS. 8A and 8B should be viewed as example but not restrictive in nature. In some implementations, the example screen shots are generated by instructions/applications downloaded to the second client device 140 by the server 106. In some implementations, the example screen shots are generated by instructions/applications that are stored on the second client device 140 (such as a browser, an assistant application, or other pre-configured application).

FIG. 8A illustrates screenshots of the first client device 102 and the second client device 140. The first client 102 displays a television program 802. After playback of the program 802 ended, the second client 140 displays an application 806 (e.g., an assistant application), one or more entities 808 related to the program 802 (e.g., top 5 people in the program 802 by popularity), and affordances 810 corresponding to the respective entities 808. While the program 802 is played on the first client 102, the first client 102 sends content information derived from the program 802 to the server system 106. Alternatively, the second client 140 sends content information derived from audio output, from the first client 102, corresponding to the program 802 to the server system 106. The server system 106 matches the content information to a content fingerprint in order to identify the program 802. After identifying a content fingerprint that matches the content information, the server 106 determines one or more entities associated with the program 802 and determines their popularities (e.g., based on number of mentions in social networks and web pages). After the program 802 finished playing, the server system 106 sends a summary with the most popular entities 808 (e.g. the top 5) and corresponding affordances 810 to the second client device 140 for presentation. The second client device 140 presents the entities 808 and corresponding affordances 810. A user may select an affordance 810 to bring up a menu of actions with respect to the corresponding entity, as with affordances 710 in FIGS. 7A-7C.

In some implementations, the most popular entities selected for the summary are the most popular in the aggregate, without any personalization to the use's interests and preferences and history. In some implementations, the most popular entities selected for the summary are the most popular, taking into account the user's interests and preferences and history as well as popularity in the aggregate.

FIG. 8B illustrates a screenshot of the second client device 140. The server system 106 determines the popularity of entities associated with video content that have been presented to users in a defined time period. The server system 106 sends a summary with the most popular entities 812 (e.g. the top 5) for the time period and corresponding affordances 814 to the second client device 140 for presentation. The second client device 140 presents the entities 812 and corresponding affordances 814. A user may select an affordance 814 to bring up a menu of actions with respect to the corresponding entity, as with affordances 810 in FIG. 8A.

It should be appreciated that the “popularity” of an entity (e.g., a quotation, etc.), as used herein, refers not merely to positive or favorable interest in the entity, but can also refer to interest in the entity more generally, as indicated by the numbers of mentions, sharing, and queries, and any other suitable criteria. Thus, the popularity metrics 460 is a measure of the level of interest in an entity.

Identifying and Storing Quotations

FIG. 9 illustrates a method 900 for identifying and storing quotations in accordance with some implementations. The method 900 is performed at a server system 106 having one or more processors and memory.

A plurality of quotations associated with media content is identified from a plurality of documents (902). The server 106 (e.g., the quotations module 148) analyzes documents (or more generally, any textual content) hosted by content hosts 170 and social networks 172 to identify quotations associated with media content items, and more specifically video content items such as movies and television programs and online videos. Examples of documents or content that are analyzed include web pages and social network profiles, timelines, and feeds. In some implementations, the documents analyzed includes particular types of documents, such as web pages that have editorial reviews, social commentary, and other online articles and documents that reference television shows and movies. In some implementations, documents in these particular categories are drawn from content hosts that are whitelisted as having these types of documents. The server system 106 analyzes the documents to find references to video content quotations and the quotations themselves.

Respective media content items associated with the quotations are identified (906). The server system 106 identifies the video content that the quotations come from, i.e., the video content in which the quotations were spoken.

In some implementations, identifying respective media content items associated with the quotations includes matching the quotations to caption data associated with the respective media content items (908). The server system 106 matches the quotations identified from the documents against subtitles data of video content. A match indicates that a quotation is associated with a video content item to which the matching subtitles data corresponds.

Respective popularity metrics of the quotations are determined in accordance with one or more popularity criteria (910). In some implementations, the popularity criteria include one or more of: a search query volume of a respective quotation, a number of mentions of the respective quotation in social networks, and a number of documents that include the respective quotation (912). The server system 106 determines the popularity metrics 460 for each identified quotation. The popularity module 150 determines the popularity of a quotation based on a number of criteria. The criteria include: how many users have searched for the quotation in a search engine 174 (the search volume of the quotation), how many times the quotation have been mentioned in social networks 172 (e.g., in social media posts and tweets), and a number of documents that include or mention the respective quotation (e.g. web pages). In some implementations, the same documents, etc. that were used in step 902 to identify quotations are analyzed to determine the popularity metrics for the quotations. In some implementations, mentions of a quotation in particular types of content, such as the particular types of documents (editorial reviews, etc.) described above in reference to step 902, are given additional weight in measuring the popularity of the quotation. In some implementations, each document (e.g., web page or website) optionally have a weight based on reputability, and mentions of a quotation by a high-reputability document are more favored. Reputability may be based on any suitable criterion or criteria, such as human curation or number of links to the document from other documents, for example.

In some implementations, the popularity module 150 also determines the popularity of quotations in real-time. For example, the popularity module 150, analyzing documents and other content for mentions and sharing of quotations and search queries for quotations and so on, can detect which quotations have recent spikes in popularity or other recent trends and changes in the popularity of a quotation.

Associations between respective quotations and respective media content items, and the respective popularity metrics of the quotations, are stored in an entities repository (914). Quotations are stored as entities 428 in the entities database 122. Each quotation entity includes references to other entities 454, which indicate associations between the quotation and the referenced entities. Each quotation entity also includes the popularity metrics 460 for the quotation as determined in step 910, and which may be periodically updated.

In some implementations, for a respective media content item, associations between one or more entities associated with the media content item and a respective quotation associated with the respective media content item are stored in the entities repository (916). As described above, the entities database 122 stores, for an entity, references to other entities, which indicate the associations between entities. In some implementations, this maps to a graph data structure within the entities database 122 that maps the connections between entities. The entities database 122 includes an entity corresponding to a video content item, which includes references to entities corresponding to people that are associated with the video content item (e.g., cast, guests, etc.). For the subset of the people associated with the video content item that had spoken dialogue in the video content item, their corresponding people entities include references to entities corresponding to quotations spoken by this subset of people. Thus, the entities database 122 stores, for a respective video content item, associations between entities associated with the video content item (e.g., people entities) and quotations associated with the video content item.

Identifying Quotations for Presentation

FIGS. 10A-10B illustrate a method 1000 for identifying quotations for presentation in accordance with some implementations. The method 1000 is performed at a server system 106 having one or more processors and memory.

A media content item currently being presented in proximity to a first user is identified (1002). The server system 106 receives content information 142 from the client 102 or 140. The content information 142 corresponds to a media content item (e.g., a video content item) being presented on client 102. It is assumed that the user is in proximity of the client 102 to be able to view the video content item, even if he is not actually viewing it. Also, as described above, the content information 142 may be derived from the audio output from the client 102 corresponding to the audio component of the video content item and perceived by a microphone on the client 140. Assuming that the user is near the client 140 (e.g., holding the client 140 in his hand), that the client 140 can perceive the audio output from the client 102 while the video content item is being played on the client 102 is an indication that the video content item is being presented in proximity to the user.

In some implementations, the identification of the media content item uses fingerprints (e.g., comparing the content information to fingerprints in the fingerprint database 120). Further details on identifying content using fingerprints are described in U.S. patent application Ser. No. 13/174,612, titled “Methods for Displaying Content on a Second Device that is Related to the Content Playing on a First Device,” filed Jun. 30, 2011, which is incorporated by reference herein in its entirety.

In some implementations, identifying the media content item currently being presented in proximity to the first user includes determining a portion of the media content item being presented in proximity to the first user (1004). The server system 106 can, not only identify the video content item being presented on the client 102, but which portion is being presented on client 102 (e.g., where in the video content item is being presented, how far from the beginning or the end of the video content item). The portion currently being presented is determined as part of the media content item identification process in step 1002; the server system 106 identifies what the media content item is and where in the media content item is currently being presented.

One or more first quotations, in an entities repository, associated with the media content item, are identified, where the first quotations are determined to be popular in accordance with one or more popularity criteria (1006). The server system 106 identifies and selects one or more quotations from the entities repository 122. These quotations are associated with the media content item; these quotations are part of the spoken dialogue within the media content item. The selected quotations are the most popular quotations associated with the media content item based on the popularity metrics 460 of the quotations determined by the server system 106. The popularity metrics are determined in accordance with one or more criteria.

In some implementations, the popularity criteria include one or more of: a search query volume of a respective quotation by the first user, an aggregate search query volume of the respective quotation, a number of mentions of the respective quotation in social networks, and a number of documents of predefined categories that include the respective quotation (1008). The criteria for determining popularity of a quotation include one or more of: how many searches for the quotation has the user and/or users in the aggregate performed (search volume), how many times has the quotation been mentioned in documents (e.g., web pages) and how many times has the quotation been shared in social networks. With respect to mentions in documents, in some implementations the server system 106 weigh more heavily mentions of the quotation in predefined categories of documents, such as web pages that contain editorial reviews, social commentary, or other web pages referencing movies and television; a mention in a document in the predefined categories of documents have more weight toward a quotation's popularity than a mention in a document outside of the predefined categories.

In some implementations, the popularity criteria include one or more realtime criteria (1010). The server system 106 can determine a real-time popularity of a quotation based on one or more real-time criteria. Real-time criteria can simply be any of the criteria described above (e.g., the criteria described in step 1008) considered with a recent time horizon. For example, search volume measured in real-time may include search volume within the last 15 minutes or minute-by-minute search volume. The real-time criteria provide a measure of recent changes, such as trends and spikes, in a quotation's popularity, i.e. the quotation's real-time popularity.

In some implementations, the first quotations are determined to be popular in real-time in accordance with the popularity criteria (1012). The server system 106 identifies and selects quotations, associated with the media content item, that are popular in real-time. In some implementations, the server system 106, when selecting quotations, consider both historical and real-time popularities and may weigh one more than the other. Note that this and other methods described herein for identifying popular quotations are also applicable to identifying other types of popular entities.

In some implementations, the first quotations are, within the media content item, proximate to the portion of the media content item being presented in proximity to the first user (1014). The server system 106, after determining the portion (representing the current playback position) of the media content item being presented (1004), identifies and selects quotations that are proximate to that portion (and that are popular as described above). A quotation is proximate to the portion of the quotation is spoken within a predefined time from the current playback position. For example, a quotation that is spoken within the last 15 minutes from the current playback position may be considered to be proximate to the portion.

In some implementations, quotations that are “proximate” to the portion being presented include quotations spoken within a time range after the current position in the media content item. The server system 106 can identify quotations that are upcoming in the media content item, further details of which are described below.

The first quotations and one or more affordances associated with the first quotations are sent to a client device associated with the first user (1016). The server system 106 sends entity information 132 to the client 140 associated with the user. The entity information 132 includes the selected quotations 708 and corresponding affordances 710. The client 140 displays the quotations 708 and the corresponding affordances 710.

Selection of a first affordance of the affordances is received, where the first affordance is associated with a respective quotation of the first quotations (1018). At the client 140, the user selects an affordance 710 corresponding to one of the quotations (e.g., affordance 710 corresponding to quotation 708-1, as shown in FIG. 7B. This opens a menu of options 712 (e.g., affordances) for performing actions associated with the quotation 708-1, as shown in FIG. 7C. The user selects one of the option affordances in menu 712, and the client 140 sends the selection to the server system 106.

In accordance with the selection of the first affordance, an operation associated with the respective quotation is performed (1020). The server system 106 performs an action in accordance with the selected affordance. For example, if the user had selected the “share quotation” option, the server system 106 makes a post sharing the quotation 708-1 in a social network 174 in which the user has an account and which the server system 106 has been given access by the user to post on the user's behalf.

In some implementations, each respective affordance provides one or more options for interacting with a respective one of the first quotations (1022). For example, when an option affordance in menu 712 is selected, additional options related to the selected option may be displayed, and the user may select any of the additional options.

In some implementations, performing an operation associated with the respective quotation includes any of: sending to a client device information related to the respective quotation for display at the client device; sharing the respective quotation; sending to a client device a media snippet that includes the respective quotation for display at the client device; initiating a search having the respective quotation as a search query; initiating a search for an entity related to the respective quotation; providing to a client device a text entry interface configured to receive input of a comment on the respective quotation; or sharing an indication of interest in the media content item, the indication of interest including the respective quotation as a caption (1024). By selecting any of the options in menu 712, the user can instruct the server system 106 to send additional information (e.g., entities) related to the quotation to the client 140 for display, share the quotation (on a social network, by email, by message, etc.), send to the client 140 a video clip that includes the quotation, perform a search with the quotation as the query, perform a search with an entity related to the quotation (e.g., the character that spoke the quotation) as the query, instruct the client device 140 to display a text input interface for inputting a comment on the quotation, or sharing an indication of interest in the video content item that includes the quotation.

In some implementations, one or more second quotations associated with a portion of the media content item succeeding the portion being presented in proximity to the first user are identified (1026), presentation of the succeeding portion in proximity to the first user is detected (1028), and, in accordance with the detection of the presentation of the succeeding portion, the second quotations and one or more affordances associated with the second quotations are sent to the client device associated with the first user (1030). As described above, quotations proximate to the current position in the video content item can include quotations spoken within a time range after the current position (i.e., succeed the current portion being presented). The server system 106 identifies these “upcoming” quotations, and waits on sending them to the client device 140 until the portion where these quotations are actually spoken is reached at the client 102. When the server system 106 detects that the portion where the “upcoming” quotations are being presented at the client 102, the “upcoming” quotations are sent to the client device 140. Thus, the server system 106 can “prefetch” quotations that come later in the video content item but hold them back until they are actually spoken in the video content item, so as not to spoil the video for the user.

Presenting Quotations

FIG. 11 illustrate a method 1100 for presenting quotations in accordance with some implementations. The method 1000 is performed at a client 140 or 182.

A media content item currently presented in proximity to a first user is detected (1102). For example, the microphone at the client device 140 perceives audio output from a client 102. An application 127 at the client device 140 derives content information 142 from the audio output and sends the content information 142 to a server system 106, where the content information 142 is matched against fingerprints in a fingerprint database 120 to identify the video content item that the audio output corresponds to. The server 106 identifies and selects quotations associated with the video content item and which are popular (e.g., has high popularity metrics 460) as determined by the server system 106. These quotations 708 and corresponding affordances 710 are sent to the client 140.

One or more popular quotations associated with the media content item and one or more corresponding affordances are displayed, where each of the affordances provides one or more options for interacting with a respective one of the popular quotations (1104). The client device 140 receives and displays the quotations 708 and the corresponding affordances 710. Each affordance 710, when activated, opens a menu 712 of options, themselves affordances, for interacting with a respective quotation 708.

User activation of a first affordance corresponding to a respective popular quotation is received (1106). In accordance with the activation of the first affordance, an operation associated with the respective popular quotation is performed (1108). The user selects an option affordance in the options menu 712, the selection of which is received by the client device 140. The client device 140, in conjunction with the server system 106, performs the action or operation corresponding to the selected affordance. For example, if the action is sharing the quotation, the server 106 shares the quotation in a social network, and the sharing process is displayed on the client device 140.

In some implementations, performing an operation associated with the respective popular quotation includes any of: displaying information related to the respective popular quotation; sharing the respective popular quotation; displaying a media snippet that includes the respective popular quotation; initiating a search having the respective popular quotation as a search query; initiating a search for an entity related to the respective popular quotation; displaying a text entry interface configured to receive input of a comment on the respective popular quotation; or sharing an indication of interest in the media content item, the indication of interest including the respective popular quotation as a caption (1110). By selecting any of the options in menu 712, the user can instruct the client device 140, in conjunction with server system 106, to send additional information (e.g., entities) related to the quotation to the client 140 for display, share the quotation (on a social network, by email, by message, etc.), send to the client 140 a video clip that includes the quotation, perform a search with the quotation as the query, perform a search with an entity related to the quotation (e.g., the character that spoke the quotation) as the query, instruct the client device 140 to display a text input interface for inputting a comment on the quotation, or sharing an indication of interest in the video content item that includes the quotation.

Generating Content Summaries

FIG. 12 illustrates a method 1200 for generating a summary of a media content item in accordance with some implementations. The method 1200 is performed at a server system 106 having one or more processors and memory.

Presentation of a media content item is detected (1202). The media content item and one or more entities related to the media content item are identified (1204). When a video content item is being presented at a client 102, the client 102 or a client 140 sends content information 142 to the server 106. The server 106 uses the content information 142 to identify the video content item. The server 106 also identifies one or more entities associated with the video content item.

Respective levels of interest in the identified entities are determined based on one or more signals (1206). The server 106 determines levels of interest (e.g., popularity metrics 460) for the identified entities using one or more signals or criteria. The server 106 determines these levels of interest in the aggregate.

In some implementations, the one or more signals include one more of: respective volumes of mentions of respective entities in documents, respective volumes of queries for respective entities, respective volumes of queries for respective media content items, an aggregate of query histories of users, and an aggregate of histories of media consumption by users (1208). The signals or criteria for determining the level of interest include search volumes for the entity and for the media content item, an aggregation of user's query histories, and an aggregation of histories of what media content items the user has consumed. Other possible signals include signals described above with respect to the determination of popularity for quotations, such as number of mentions in documents and sharing in social networks.

In some implementations, the signals include one or more of: a location of the user, demographic characteristics of the user, a query history of the user, and a media consumption history of the user (1210). The signals may include signals that are specific to the user, such as the location, demographic information of the user, the user's query history, and the user's history of consumption of media content items.

In some implementations, determining respective levels of interest in the identified entities based on one or more signals includes determining respective levels of interest in the identified entities with respect to the user (1212). When the user-specific signals described in step 1210 are used along with other signals (e.g., those described in step 1208 above), the server 106 can determine levels of interest for the entities with respect to the user as well as in the aggregate.

A subset of the entities is selected based on the determined levels of interest (1214). The server 106 selects the entities associated with the media content item with high aggregate levels of interest (e.g., top 5 in level of interest).

In some implementations, selecting a subset of the entities includes selecting a subset of the entities based on the determined levels of interest with respect to the user (1216). The server 106 can select the entities associated with the video content item that the user is more interested in, rather than those that have high aggregate levels of interest. Alternatively, the server 106, when selecting the entities, consider both the user's and the aggregate levels of interest, but weights the user's levels of interest more highly. Either way, the server 106 selects entities in a way that is more personalized to the user.

The selected subset of the entities is sent to a client device of a user for presenting at the client device (1218). The selected entities 808 are sent, as a summary of the media content item 802, to the client device 140 for display at the client device 140.

FIG. 13 illustrates a method 1300 for generating a summary of media content items with respect to a time period in accordance with some implementations. The method 1300 is performed at a server system 106 having one or more processors and memory.

Presentation of a plurality of media content items is detected (1302). The media content items and, for each respective media content item, one or more entities related to the respective media content item are identified (1304). When video content items are being presented at client devices of users, the client devices (e.g., client 102 or 140) send content information 142 for the video content items to the server 106. The server 106 uses the content information 142 to identify the video content items. The server 106 also identifies one or more entities associated with each respective identified video content item.

Respective levels of interest in the identified entities are determined with respect to a defined time period based on one or more signals (1306). The server 106 determines levels of interest (e.g., popularity metrics 460) for the identified entities using one or more signals or criteria. The server 106 determines these levels of interest in the aggregate and with respect to a defined time period (e.g., level of interest in the defined time period). The signals used may be the same as those described above with reference to FIG. 12.

In some implementations, the defined time period is any of: a defined hour, a defined day, a defined month, or a defined time range (1308). The level of interest for an entity may be determined with respect to a defined hour or hours (e.g., the 8-AM-hour), a defined day or days (e.g., Mondays), a defined month or months (e.g., May), or a defined time range (e.g., the “prime time” hours). The defined time period may also be a combination of the above. For example, the defined time period may be a defined time range on a defined day (e.g., “prime time” hours on Thursdays).

A subset of the entities is selected based on the determined levels of interest with respect to the defined time period (1210). The server 106 selects the entities, associated with the media content items, with high aggregate levels of interest within the defined time period (e.g., top 5 in level of interest for the defined time period).

The selected subset of the entities is sent to a client device of a user for presenting at the client device (1212). The selected entities 812 are sent, as a summary of the media content items for the defined time period, to the client device 140 for display at the client device 140.

In some implementations, a summary includes top stories (e.g., news stories). For example, the server 106 identifies the entities within the media content item. The server 106 searches for stories (e.g., documents containing news articles, etc.) that mention the entities and which are popular. The server 106 identifies the most popular of these documents and includes them in the summary. In some implementations, stories for entities are identified by identifying important keywords in stories (e.g., people and places mentioned in the stories). Stories that share important keywords are clustered together. These important keywords are matched against the content of the media content item (e.g., the subtitles data) to find stories related to entities related to the media content item. The popularities of these stories are determined, and the most popular are displayed in the summary.

In some implementations, a summary of the media content item is generated and displayed in real time. For example, as the media content item is being presented, the media content item and the current presentation/playback position of the media content item are detected. The server 106 generates a summary of a time range from the current presentation position (e.g., the last 15 minutes) and sends the summary to the client device 140 for presentation to the user. This summary is continuously updated or refreshed as the media content item is being presented.

In some implementations, the presentation of information related to quotations and of content summaries, as described above, can be performed in response to a search query by the user as well as in response to watching of a media content item. For example, when the user searches for a quotation from a television show (e.g., submits the quotation as a query to a search engine 174), the server 106 receives the quotation query (e.g., the search engine 174 sends the query to the server 106), and identifies information related to the quotation (e.g., the quotation-related information as described above). The quotation-related information may be displayed in addition to, or in lieu of, the search results. Similarly, if the user searches for a television show, a summary of the show (e.g., for the most recent episode, for the last month, etc.) may be displayed in addition to, or in lieu of, the search results.

In some implementations, the server 106 builds the entities database 122 by analyzing media content items and referencing data from other sources (e.g., online documents, other information services). The analysis of the media content items includes receiving, retrieving, or extracting, for example, data corresponding to the audio track, subtitles data, and metadata from the media content items. From the audio track data etc., the server 106 identifies entities mentioned or appearing in the media content items (e.g., people, places, music, quotations, etc.) and when in the media content items do these entities appear or are mentioned. For example, the server 106 may treat any proper noun mentioned in the audio track data etc. as a potential entity, and reference other information and data sources to confirm. The server 106 may search documents (e.g., web pages) for mentions of potential entities found in the audio track data etc. for the media content items. If the number of mentions in the documents and, optionally, quality of these mentions, exceed a threshold, the potential entity is confirmed as an entity for addition to the entities database 122. Additionally, the server 106 may reference other sources of data to assist in the identification. For example, the server 106 may refer to a music information source (e.g., a song/music identification service, a music database) to assist in the identification of music played or mentioned in the media content items.

It will be understood that, although the terms “first,” “second,” etc. may be used herein to describe various elements, these elements should not be limited by these terms. These terms are only used to distinguish one element from another. For example, a first contact could be termed a second contact, and, similarly, a second contact could be termed a first contact, which changing the meaning of the description, so long as all occurrences of the “first contact” are renamed consistently and all occurrences of the second contact are renamed consistently. The first contact and the second contact are both contacts, but they are not the same contact.

The terminology used herein is for the purpose of describing particular implementations only and is not intended to be limiting of the claims. As used in the description of the implementations and the appended claims, the singular forms “a”, “an” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will also be understood that the term “and/or” as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items. It will be further understood that the terms “comprises” and/or “comprising,” when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.

As used herein, the term “if” may be construed to mean “when” or “upon” or “in response to determining” or “in accordance with a determination” or “in response to detecting,” that a stated condition precedent is true, depending on the context. Similarly, the phrase “if it is determined [that a stated condition precedent is true]” or “if [a stated condition precedent is true]” or “when [a stated condition precedent is true]” may be construed to mean “upon determining” or “in response to determining” or “in accordance with a determination” or “upon detecting” or “in response to detecting” that the stated condition precedent is true, depending on the context.

Reference will now be made in detail to various implementations, examples of which are illustrated in the accompanying drawings. In the following detailed description, numerous specific details are set forth in order to provide a thorough understanding of the invention and the described implementations. However, the invention may be practiced without these specific details. In other instances, well-known methods, procedures, components, and circuits have not been described in detail so as not to unnecessarily obscure aspects of the implementations.

The foregoing description, for purpose of explanation, has been described with reference to specific implementations. However, the illustrative discussions above are not intended to be exhaustive or to limit the invention to the precise forms disclosed. Many modifications and variations are possible in view of the above teachings. The implementations were chosen and described in order to best explain the principles of the invention and its practical applications, to thereby enable others skilled in the art to best utilize the invention and various implementations with various modifications as are suited to the particular use contemplated. 

What is claimed is:
 1. A method, comprising: at a server system having one or more processors and memory storing one or more programs for execution by the one or more processors: detecting presentation of a media content item at a first client device in proximity to a second client device, including receiving from the second client device content identification information; identifying the media content item based on the content identification information; identifying a plurality of entities related to the identified media content item; for each of the plurality of entities; determining a level of interest of a user of the second client device in the entity based on one or more signals of interest from the user of the second client device with respect to the entity; determining respective levels of interest of other users in the entity based on respective signals of interest from the other users with respect to the entity; and computing an aggregated popularity for the entity, the aggregated popularity including an aggregate of the level of interest of the user and the respective levels of interest of the other users, wherein the level of interest of the user is given greater weight than the respective levels of interest of the other users in the aggregated popularity; selecting a subset of the plurality of entities based on the aggregated popularity for each of the entities; and sending to the second client device, for presenting at the second client device, a listing of the selected subset of the entities.
 2. The method of claim 1, wherein the level of interest is based on a defined time period.
 3. The method of claim 1, wherein the respective levels of interest of the other users include one or more of: a volume of mentions of the entity in documents, a volume of queries for the entity, a volume of queries for the media content item, an aggregate of query histories of users, and an aggregate of histories of media consumption by users.
 4. The method of claim 2, wherein the defined time period is any of: a defined hour, a defined day, a defined month, or a defined time range.
 5. The method of claim 1, further comprising: continuously updating the listing of the selected subset of the entities as the media content item is being presented.
 6. The method of claim 1, wherein identifying the media content item further comprises identifying a current position of the media content being presented at the first client device.
 7. The method of claim 1, wherein the plurality of entities include a plurality of: titles, people, places, music, things, products, quotations, and awards.
 8. The method of claim 1, wherein each of the plurality of entities corresponds to a respective proper noun associated with the media content item.
 9. A non-transitory computer readable storage medium storing one or more programs, the one or more programs comprising instructions that, when executed by a server system, cause the server system to perform operations comprising: detecting presentation of a media content item at a first client device in proximity to a second client device, including receiving from the second client device content identification information; identifying the media content item based on the content identification information; identifying a plurality of entities related to the identified media content item; for each of the plurality of entities: determining a level of interest of a user of the second client device in the entity based on one or more signals of interest from the user of the second client device with respect to the entity; determining respective levels of interest of other users in the entity based on respective signals of interest from the other users with respect to the entity; and computing an aggregated popularity for the entity, the aggregated popularity including an aggregate of the level of interest of the user and the respective levels of interest of the other users, wherein the level of interest of the user is given greater weight than the respective levels of interest of the other users in the aggregated popularity; selecting a subset of the plurality of entities based on the aggregated popularity for each of the entities; and sending to the second client device, for presenting at the second client device, a listing of the selected subset of the entities.
 10. The non-transitory computer readable storage medium of claim 9, the operations further comprising: maintaining a media content identification database for a corpus of media content items, the corpus of media content items including the media content item, wherein the media content identification database comprises a collection of content fingerprints that are generated from content of the corpus of media content items.
 11. The non-transitory computer readable storage medium of claim 10, wherein the collection of content fingerprints comprises fingerprints generated from one or more of: a signature of a video stream and/or an audio stream, captions data corresponding to the video stream and/or the audio stream, and a portion of the video stream and/or the audio stream.
 12. The non-transitory computer readable storage medium of claim 10, wherein the collection of content fingerprints includes a name and a list of files associated with the name.
 13. The non-transitory computer readable storage medium of claim 12, wherein the collection of content fingerprints further includes fingerprint audio information and/or fingerprint video information associated with the name.
 14. The non-transitory computer readable storage medium of claim 10, the operations further comprising updating the collection of content fingerprints with respect to a defined time period.
 15. The non-transitory computer readable storage medium of claim 9, wherein the computing the aggregated popularity for the entity is with respect to a defined time period; and wherein the defined time period is any of: a defined hour, a defined day, a defined month, or a defined time range.
 16. The non-transitory computer readable storage medium of claim 10, wherein identifying the media content item based on the content identification information comprises: matching the content identification information to the media content identification database, including: formatting the content information; and comparing the formatted content information to the media content identification database.
 17. A server system, comprising: memory; one or more processors; and one or more programs stored in the memory and configured for execution by the one or more processors, the one or more programs including instructions for: detecting presentation of a media content item at a first client device in proximity to a second client device, including receiving from the second client device content identification information; identifying the media content item based on the content identification information; identifying a plurality of entities related to the identified media content item; for each of the plurality of entities: determining a level of interest of a user of the second client device in the entity based on one or more signals of interest from the user of the second client device with respect to the entity; determining respective levels of interest of other users in the entity based on respective signals of interest from the other users with respect to the entity; and computing an aggregated popularity for the entity, the aggregated popularity including an aggregate of the level of interest of the user and the respective levels of interest of the other users, wherein the level of interest of the user is given greater weight than the respective levels of interest of the other users in the aggregated popularity; selecting a subset of the plurality of entities based on the aggregated popularity for each of the entities; and sending to the second client device, for presenting at the second client device, a listing of the selected subset of the entities.
 18. The system of claim 17, further comprising instructions for maintaining at the server system an entities database, the entities database including: titles, people, places, music, products, quotations and awards.
 19. The system of claim 17, wherein the entities database further comprises a graph network that indicates associations between entities.
 20. The system of claim 17, wherein the one or more signals from the user of the second client device comprise one or more of: a location of the user of the second client device, demographic characteristics of the user of the second client device, a query history of the user of the second client device, and a media consumption history of the user of the second client device. 